Comparison
gpt-neox vs litgpt
Verdict
Pick gpt-neox if gPT-NeoX is a model parallel autoregressive transformer implementation on GPUs, leveraging Megatron and DeepSpeed libraries; pick litgpt if litgpt offers a suite of over 20 high-performance large language models, with tools for pretraining, finetuning, and deployment at scale, all under the Apache-2.0 license.
Markdown twin · gpt-neox alternatives · litgpt alternatives
GraphCanon updated Sep 20, 2026
13views this month
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Trust & integrity
| Signal | gpt-neox | litgpt |
|---|---|---|
| Maintenance | Active (13d since push) As of Sep 18, 2026 · github_public_v1 | Very active (3d since push) As of Sep 18, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 18, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 18, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Sep 18, 2026 · osv@v1 | No lockfile (source not queried) As of Sep 18, 2026 · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- gpt-neox
- Model parallel autoregressive transformers on GPUs
- litgpt
- High-performance LLMs for pretraining, finetuning, and deployment
Stars
- gpt-neox
- 7.5k
- litgpt
- 14k
Forks
- gpt-neox
- 1.1k
- litgpt
- 1.5k
Open issues
- gpt-neox
- 118
- litgpt
- 290
Language
- gpt-neox
- Python
- litgpt
- Python
Adopt for
- gpt-neox
- GPT-NeoX is a model parallel autoregressive transformer implementation on GPUs, leveraging Megatron and DeepSpeed libraries.
- litgpt
- litgpt offers a suite of over 20 high-performance large language models, with tools for pretraining, finetuning, and deployment at scale, all under the Apache-2.0 license.
Persona
- gpt-neox
- -
- litgpt
- -
Runtime
- gpt-neox
- -
- litgpt
- -
License
- gpt-neox
- GPT-NeoX is licensed under the Apache License, Version 2.0, which allows for free use, modification, and distribution of the software, provided that the license terms are adhered to.
- litgpt
- Apache-2.0
Last pushed
- gpt-neox
- Sep 4, 2026
- litgpt
- Sep 14, 2026
Categories
- gpt-neox
- LLM Frameworks, Model Training
- litgpt
- Inference & Serving, LLM Frameworks, Model Training
Trust and health
Maintenance
- gpt-neox
- Active (82%)
- litgpt
- Very active (96%)
Days since push
- gpt-neox
- 13d
- litgpt
- 3d
Open issues (now)
- gpt-neox
- 118
- litgpt
- 290
Stars delta
- gpt-neox
- +9 (30d)
- litgpt
- +62 (30d)
Open issues delta
- gpt-neox
- +7 (30d)
- litgpt
- +18 (30d)
Full report
- gpt-neox
- Trust report
- litgpt
- Trust report
Choose gpt-neox if…
- Requirements: Min 16 GB RAM; Requires GPU support for optimal performance.; Integration with Megatron and DeepSpeed libraries is essential for full functionality..
- Tags unique to gpt-neox: autoregressive-transformers, deepspeed-library, gpt-3, gpu.
- When you need to train large language models on GPUs and require model parallelism to handle the computational demands.
When NOT to use gpt-neox
- If your project does not require the scale of model parallelism and can be handled with single-GPU setups, GPT-NeoX might introduce unnecessary complexity.
- When the specific features of Megatron and DeepSpeed are not aligned with your project's needs, opting for a simpler framework might be more suitable.
Choose litgpt if…
- Tags unique to litgpt: ai, artificial-intelligence, deep-learning, large-language-models.
- Also covers Inference & Serving.
- When you need a comprehensive set of over 20 high-performance LLMs for pretraining, finetuning, and deployment.
When NOT to use litgpt
- If you are looking for a tool that supports languages other than Python, as litgpt is exclusively Python-based.
- When you need a tool that offers fewer model options, as litgpt provides over 20 models which might be overwhelming for specific use cases.
- If you require proprietary licensing, as litgpt is open-source under the Apache-2.0 license.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (EleutherAI/gpt-neox) · observed Sep 20, 2026
- GitHub forks (EleutherAI/gpt-neox) · observed Sep 20, 2026
- Last push (EleutherAI/gpt-neox) · observed Sep 4, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 18, 2026
- Trust scan (lockfile / OSV) · observed Sep 18, 2026
- GitHub stars (Lightning-AI/litgpt) · observed Sep 20, 2026
- GitHub forks (Lightning-AI/litgpt) · observed Sep 20, 2026
- Last push (Lightning-AI/litgpt) · observed Sep 14, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 18, 2026
- Trust scan (lockfile / OSV) · observed Sep 18, 2026
GitHub stars on cards: gpt-neox 7.5k · litgpt 14k (synced Sep 20, 2026).
Common questions
- What is the difference between gpt-neox and litgpt?
- gpt-neox: Model parallel autoregressive transformers on GPUs. litgpt: High-performance LLMs for pretraining, finetuning, and deployment. See the comparison table for live GitHub stats and shared categories.
- When should I choose gpt-neox over litgpt?
- Choose gpt-neox over litgpt when Requirements: Min 16 GB RAM; Requires GPU support for optimal performance.; Integration with Megatron and DeepSpeed libraries is essential for full functionality.; Tags unique to gpt-neox: autoregressive-transformers, deepspeed-library, gpt-3, gpu; When you need to train large language models on GPUs and require model parallelism to handle the computational demands.
- When should I choose litgpt over gpt-neox?
- Choose litgpt over gpt-neox when Tags unique to litgpt: ai, artificial-intelligence, deep-learning, large-language-models; Also covers Inference & Serving; When you need a comprehensive set of over 20 high-performance LLMs for pretraining, finetuning, and deployment.
- When should I avoid gpt-neox?
- If your project does not require the scale of model parallelism and can be handled with single-GPU setups, GPT-NeoX might introduce unnecessary complexity. When the specific features of Megatron and DeepSpeed are not aligned with your project's needs, opting for a simpler framework might be more suitable.
- When should I avoid litgpt?
- If you are looking for a tool that supports languages other than Python, as litgpt is exclusively Python-based. When you need a tool that offers fewer model options, as litgpt provides over 20 models which might be overwhelming for specific use cases. If you require proprietary licensing, as litgpt is open-source under the Apache-2.0 license.
- Is gpt-neox or litgpt more popular on GitHub?
- litgpt has more GitHub stars (13,667 vs 7,461). Stars measure visibility, not whether either tool fits your constraints.
- Are gpt-neox and litgpt open source?
- Yes - both are open-source projects on GitHub (gpt-neox: Apache-2.0, litgpt: Apache-2.0).
- Where can I find alternatives to gpt-neox or litgpt?
- GraphCanon lists graph-backed alternatives at gpt-neox alternatives and litgpt alternatives (gpt-neox markdown twin, litgpt markdown twin), ranked by typed relationship edges rather than popularity votes.
- Is there a machine-readable version of this comparison?
- Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, gpt-neox or litgpt?
- gpt-neox: Active. litgpt: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
- Where are the full trust reports for gpt-neox and litgpt?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: gpt-neox trust report; litgpt trust report.